Does Data Really Save Lives? Considerations in Digitising Health


To: Simon Bolton, CEO of NHS Digital 

Boar Lane, 

Leeds, West Yorkshire,


Dear Mr. Bolton,

“Data saves lives” has played a central role in NHS messaging since the pandemic and continues to be a driving factor behind the NHS’ digitisation initiatives. Whilst I applaud the forward thinking and acceptance of necessary new technologies within the NHS, I am writing in reference to the NHS Long Term Plan and the underlying General Practice Data for Planning and Research (GPDPR) initiatives. How are the timelines looking?

            Contrary to most letters you might get telling you to hurry up, I believe pushing back the timeline on implementing the GPDPR was the right decision to make. Since the Long Term Plan’s interim goals for 90% of integrated care systems (ICSs) and NHS trusts to have electronic health records (EHRs) by December 2023 seem to be unfinished (NHS Digital), holding on the GPDPR allows for more time to examine the “datafication” of health before it is too late. I am a student in an Applied Medical Anthropology module at UCL, and my combined experience with medtech start-ups has demonstrated the importance of this issue in the practice of socially salient healthcare. The EHRs would play an instrumental role in defining what and how personal patient data gets stored and circulated, but most importantly, how it gets used. 

Currently, the NHS employs 21 different EHR providers across its trusts – all with different interfaces, modules, and no interoperability of data (Walsh, 2004). This data is mostly hosted on local legacy systems, but when it does get shared (as in the case of the GPDPR), individuals may find themselves subjected to unpaid and invisible “digital labour” in their role as data sources. (Lupton, 2017) Data’s role in the modern economy shapes and permeates power over all facets of everyday life, but the health-data ecosystem especially factors into the extensive biomedicalization of personhood. Michel Foucault utilises the terms “biopower” and the “medical gaze” to describe the effect that datafication and eventual commodification of bodies has on individuals undergoing medical processes. (Ruckenstein and Schüll, 2017) Often covert, the medical gaze attaches socially prescribed meanings onto individuals’ data, which poses issues when it is the only sort of information stored and thus available to healthcare providers. Lupton (2012) argues that the tools of mHealth and digital devices amplify not only the medical gaze, but “surveillance society” more generally, allowing those with economic and political power to “intimately dictate everyday behaviours”. 

With the introduction of commercial players into the EHR and mHealth space, patients increasingly see themselves as providers of “biocapital” through their data: their vital signs, prescription data, and diagnoses contribute to the commodification of their bodies. As you will know, this has been evidenced most clearly through the more than a million people who opted out of the GPDPR scheme two summers ago. (Jayanetti, 2021) The point is, the datafication of health is reducing public trust in the NHS, and this is an issue that can be addressed. People want to see a more socially salient form of healthcare, one that uses EHRs as a form of therapeutic understanding rather than erasing their narratives. Ventres et. al (2006) conducted an ethnographic study in primary care offices located in the Pacific Northwest to determine if the dominant discourse that EHRs made physicians structure interactions around data-gathering rather than patients’ stories were true, and his results shed light onto how the NHS may approach digitisation while respecting patient comfort. Often, the presence of computers and immediately available EHR intimidated patients, who felt as if they were being assessed or judgements were being made on them without their knowledge. One clinician described the EHR as the “third party” in the encounter, altering the relationship with the patient as most communication had to be transcribed onto the EHR before follow-up questions. Most of the discomfort from such a closeness of technology stems from underlying patient assumptions that EHRs quantify their lived experiences in such a way that prevents doctors from actually “listening” to them. 

While currently misunderstood, the EHR acts as a barrier to empathy for some and would prolong the amount of time required to make a diagnosis as patients would be willing to divulge less. Going back to the type of data that EHRs collect, the metrics focus on clinical competencies rather than sociocultural understanding, which may mistakenly push dominant and harmful narratives relating to a group of people. Building this social understanding won’t be easy – this means greater investment into the medics themselves, diversity training, and a wider focus on the literature of medical anthropology in which health is examined through a different lens. Drawing from this analysis, the NHS can adopt a wider-ranging educational campaign that reinforces the human relationship that is aided by technology, not the other way around. Perhaps a greater focus on GPs who have benefitted from the accessibility of EHRs or testimonials regarding how much easier the processes have been made, would convince the public of the positives of sharing their data. 

Xinyuan Wang’s (2016) work on mHealth in China brings up another consideration with “big data” that is often overlooked: the hidden workload of nurses scrambling to maintain these databases and make sense of the metrics, and those that get left behind. In his study of an elder care centre, there was the practice of recording more than 50 types of health data every day, some automatically updated from the bed patients slept on, others on the type of food/medication they had, etc. However, other social information such as the patients’ life trajectories, hobbies, preferences, even the type of music they liked/calmed them down – these were solely dependent on the emotional labour of the caretakers to track. Even though this data was essential in providing holistic care, because of the “focus on data-centred professionalism”, the official systems neglected information that contributed to a fuller understanding of health. These points were also lost with the caretakers if their schedules changed or they were reallocated, resulting in a loss of productivity and efficiency in needing to “know” the patient again. The datafication of health is therefore a double-edged sword; it calls for more resources and importance attributed to non-material stories, but in this way it also requires a deeper patient-physician understanding of privacy and purposes. 44% of people trust that the NHS is providing good service nationally (The Health Foundation, 2022), which demonstrates that this is the central barrier and question the NHS must answer before turning to digitisation.

Going back to socially salient healthcare, this goes hand in hand with the “paradox of trust” (adapted from Keynes’ “paradox of thrift”) that establishes why the datafication of health is facing such resistance when it has its merits. The paradox operates as “governments design publicly structured systems of health care and social welfare behind which lie for-profit private providers, leaving public trust […] impossible to generate because the main aim of these providers is to compound gains for investors by giving less”. (Napier et. al, 2014) This creates a distinctly biopolitical landscape, one which places care at the crux of capitalistic needs, influencing how health is valued and understood in relation to an availability of resources. Viewing health through a monetary lens also places social meanings onto the prescription of health, diseases, and treatment. As a public healthcare provider, the NHS needs to be distinctly aware of the connotations associated with stigmatising or ostracising certain types of healthcare (such as dental care, one of the only NHS services that needs to be paid for by patients). In line with GDPR regulations, the paradox of trust makes it hard for patients to access holistic healthcare because of the decentralisation of services and prohibition of personally identifiable information. With the focus on private providers in public health, datafication seeks to then make individuals proxy to neoliberal subjectification, seeing them reclaim their agency in making an enterprise of their own data. (Burcher et. al, 1991) 

Most importantly, individuals need to be given the ownership of their own data in healthcare systems, allowing them to utilise the datafication as a “technology of the self”. (Ruckenstein and Schüll, 2017) Using this framework to understand how and why patients would choose to revoke access from the GPDPR, the NHS should take into account the social and cultural resistance the Long Term Plan would face as well and factor this into timelines respectively. Apart from educating the public and being transparent on how data collection and processing would work, I believe that the NHS still has some way to go in first prioritising a holistic understanding of health that includes social, cultural, and economic considerations when administering medicine. Only once all aspects of health and wellbeing are considered should the NHS start towards a shift in paradigm to digital competencies and add-ons. After all, health is what we make it to be – and so is technology.

Thank you for taking the time to review this letter.

Yours sincerely,

Serene Lim

Reference List

Burchell, G., Miller, P. and Gordon, C. (1991). The Foucault effect : studies in governmentality. Chicago, Ill.: The University Of Chicago Press, pp.87–104.

Department of Health and Social Care (2022). A Plan for Digital Health and Social Care. [online] GOV.UK. Available at:

Jayanetti, C. (2021). NHS data grab on hold as millions opt out. [online] the Guardian. Available at:

Lupton, D. (2012). M-health and health promotion: The digital cyborg and surveillance society. Social Theory & Health, 10(3), pp.229–244.

Lupton, D. (2017). Digital Health : Critical and Cross-Disciplinary Perspectives. Routledge. (n.d.). Electronic health records – MHRA Inspectorate. [online] Available at:

Napier, A.D., Ancarno, C., Butler, B., Calabrese, J., Chater, A., Chatterjee, H., Guesnet, F., Horne, R., Jacyna, S., Jadhav, S., Macdonald, A., Neuendorf, U., Parkhurst, A., Reynolds, R., Scambler, G., Shamdasani, S., Smith, S.Z., Stougaard-Nielsen, J., Thomson, L. and Tyler, N. (2014). Culture and health. The Lancet, [online] 384(9954), pp.1607–1639. Available at:

NHS Digital (2021). General Practice Data for Planning and Research (GPDPR). [online] NHS Digital. Available at:

Ruckenstein, M. and Schüll, N.D. (2017). The Datafication of Health. Annual Review of Anthropology, 46(1), pp.261–278.

The Health Foundation (2022). Public perceptions of the NHS and social care: performance, policy and expectations – The Health Foundation. [online] Available at:

Ventres, W. (2006). Physicians, Patients, and the Electronic Health Record: An Ethnographic Analysis. The Annals of Family Medicine, [online] 4(2), pp.124–131. Available at: [Accessed 19 Dec. 2019].

Walsh, S.H. (2004). The clinician’s perspective on electronic health records and how they can affect patient care. BMJ : British Medical Journal, [online] 328(7449), pp.1184–1187. Available at: [Accessed 7 Feb. 2021].

Wang, X. (2016). Social media in industrial China. London: UCL Press.

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Photo by Alexander Sinn on Unsplash

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